Using spreading activation to understand repetitive negative thinking

Abstract

ABSTRACT Repetitive negative thinking (RNT) describes a recursive, unproductive pattern of thought that is commonly observed in individuals who experience anxiety and depression. Past research on RNT has primarily relied on self-report, which fails to capture the potential mechanisms that underlie the persistence of maladaptive thought. We investigated whether RNT may be maintained by a negatively biased semantic network. The present study used a modified free association task to assess state RNT. Following the presentation of a valenced (positive, neutral, negative) cue word, participants generated a series of free associates, which allowed for the dynamic progression of responses. State RNT was conceptualised as the length of consecutive, negatively valenced free associates (i.e. chains). Participants also completed two self-report measures that assessed trait RNT and trait negative affect. Within a structural equation model, negative (but not positive or neutral) response chain length positively predicted trait RNT and negative affect, and this was only the case for positive (but not negative or neutral) cue words. These results suggest that RNT tendencies may be reflected in semantic retrieval and can be assessed without self-report.